cli-forge-pipelinelisted

Expert CI/CD pipeline optimizer using biomimetic patterns from nature: leafcutter ants (task partitioning), slime mold (adaptive path optimization), army ants (self-organizing parallelism), honeybees (dynamic resource allocation), and mycelium (fault-tolerant routing). Works with any CI system — examples cover both GitLab CI and GitHub Actions. Use this skill whenever the user asks to optimize, design, review, speed up, parallelize, or fix a CI/CD pipeline. Also triggers on: "slow pipeline", "flaky tests", "runners", "artifacts", "CI cache", "parallel build", "GitLab CI", "GitHub Actions", "pipeline design", "reduce build time", DAG pipelines, job dependencies, or any request mixing infrastructure + automation + deployment. Use it even when the user just pastes a YAML pipeline without asking explicitly.
Destynova2/cli-code-skills · ★ 4 · Data & Documents · score 83

Install: claude install-skill Destynova2/cli-code-skills

> **Optimization:** This skill uses on-demand loading. Heavy content lives in `references/` and is loaded only when needed. > **Language rule:** Skill instructions are written in English. When generating user-facing output (reports, files, documentation), detect the project's primary language (from README, comments, docs, commit messages) and produce the output in that language. If the project is bilingual, ask the user which language to use before proceeding. # CI Pipeline Optimizer — Biomimetic > *"The leafcutter ant colony has no project manager. > Yet it optimally relocates 15% of all tropical vegetation."* ## The 9 biological models → CI patterns Read `references/patterns.md` for detailed explanations, biology, and dual GitLab/GitHub examples. | # | Organism | CI Pattern | Key principle | |---|----------|------------|---------------| | 1 | **Leafcutter ants** (Atta) | Stage Specialization + Artifact Cache | Each job = one role. Artifacts = stigmergy | | 2 | **Slime mold** (Physarum) | Change-Driven Path Selection + Cache Reinforcement | Only rerun what changed. Content-hashed cache | | 3 | **Army ants** (Eciton) | Fan-out / Fan-in + Ephemeral Runners | Maximum parallelism, disposable runners | | 4 | **Honeybees** (Apis) | Autoscaling + Priority-based Runner Tagging | Resources proportional to load | | 5 | **Mycelium** | Multi-Registry Fallback + Distributed Cache | Zero SPOF, waterfall cache | | 6 | **Mitosis** | Workflow Fission | Pipeline too big → split into ind